Quack! DuckDB for Data Professionals

If you regularly use Pandas for your data analysis and wrangling tasks, it's time to start using DuckDB.

What is DuckDB?

DuckDB is an in-memory, open-source OLAP SQL database management system designed for interactive querying and high-speed data processing. It seamlessly integrates with Python and R, offering excellent compatibility with popular data packages like Pandas and dplyr.

Why Should You Use DuckDB?

1. Simplicity: Like SQLite, DuckDB requires no external dependencies. It's easy to set up and integrate into your projects. To install you just need to run pip

pip install duckdb        

1. Speed: This is what I love most about DuckDB. Its columnar-vectorized query engine processes large batches of values (a "vector") in one operation, dramatically speeding up query execution.
2. Feature-Rich: DuckDB supports complex SQL queries and guarantees ACID properties (Atomicity, Consistency, Isolation, Durability). It handles multiple input/output formats like CSV, Parquet, JSON, and can read from HTTPS, S3, GCS, and databases like PostgreSQL and SQLite. Plus, it supports the PostgreSQL dialect and offers unique SQL features.
3. Portability: With no dependencies, DuckDB is extremely portable and can be compiled for all major operating systems (Linux, macOS, Windows).

My Experience

I recently tested DuckDB by loading data from a movies CSV into a PostgreSQL database—a task many of us perform regularly. I compared the performance between Pandas and DuckDB, and the results were astonishing:

• DuckDB loaded the data in 0.24 seconds.

• Pandas took 4.2 seconds.

That's a 17x speed improvement with DuckDB!

With DuckDB, you can leverage on the powerful and expressive SQL language without having to worry about moving your data in – and out – of Pandas

If you're interested in trying this out, you can get the dataset from Kaggle and the script from my GitHub.

Conclusion

DuckDB has become an essential tool for me.

It's not a replacement for Pandas; instead, the two complement each other as you can switct from Pandas to Duckdb and vice versa.

For any data professional proficient in SQL, incorporating DuckDB into your workflow is a game-changer.